Many existing computing systems include a traditional camera as an integrated peripheral device. A current trend is to enhance computing system imaging capability by integrating depth capturing into its imaging components. Depth capturing may be used, for example, to perform various intelligent object recognition functions such as facial recognition (e.g., for secure system un-lock) or hand gesture recognition (e.g., for touchless user interface functions).
One depth information capturing approach, referred to as “time-of-flight” imaging, emits (e.g., infra-red (IR)) light from a system onto an object and measures, for each of multiple pixels of an image sensor, the time between the emission of the light and the reception of its reflected image upon the sensor. The image produced by the time of flight pixels corresponds to a three-dimensional profile of the object as characterized by a unique depth measurement (z) at each of the different (x,y) pixel locations. Other types of depth capturing approaches include stereo triangulation, sheet of light triangulation and structured light.
Depending on implementation, some depth capturing cameras may be able to also take traditional 2D images within the field of view of the camera. For example, a time-of-flight camera may also include visible light color pixels (e.g., Bayer patterned red (R), blue (B) and green (G) pixels) integrated on a same image sensor with pixels that detect the light used for the time-of-flight measurement).